Mobility is a critical component of independence and the quality of life of older persons. A significant number of older persons with mobility impairment demonstrate ischemic lesions in brain white matter (WM). We hypothesize that: Ss with a high level of vascular disease risk factors, will have a larger initial volume and higher accrual rate of WMSA; impaired mobility is caused by site-specific WMSA damaging fronto-parietal periventricular WM and WMSA accrual rate is stable allowing prediction of Ss "at risk" for large WMSA increases. The link between ischemic WM lesions, which appear on MRI as WM signal abnormality (WMSA), and vascular disease risk factors (VDRF), as a cause, requires better definition. We propose to link VDRF to mobility impairment associated with WMSA and then determine if the risk factors predict incident cases. This will allow us to assess the magnitude of the VDRF as a cause of mobility impairment in order to plan new treatment strategies. We will use quantitative MRI and quantitative measures of mobility to link WMSA to mobility disorders. In preliminary studies, we separated older persons into groups with normal and impaired mobility. Automated quantitative segmentation of their MR images showed an increased volume of WMSA correlates with poorer mobility but not with age suggesting that the accrual of WMSA is related to a disease process. Site-specific periventricular WMSA involving frontal and parieto-occipital regions were present in Ss with impaired mobility. Follow-up MRIs on 14 Ss, 20 months after the initial scan, showed WMSA accrual was related to WMSA volume at baseline suggesting a continuous process and that the volume of WMSA increased at a fivefold greater rate in mobility impaired compared to normal Ss. We have recently determined that the quantitative measures of mobility are reliable. To move beyond correlation, we are proposing a 5- year project with 2 components: a cross-sectional analysis of 99 Ss 70 years and older stratified by mobility followed by a 4-year longitudinal follow-up. The cross-sectional component will determine the relationship of vascular disease risk factors, WMSA volume, WMSA location, use diffusion tensor imaging to identify/quantify damage to WM pathways and quantitative measures of mobility. Using the same measures, the longitudinal component will: 1) establish the link between vascular disease risk factors and mobility impairment; 2) establish clinical predictive value of imaging; 3) evaluate the causal relationship of WMSA to mobility; 4) refine our understanding of the anatomic substrate of mobility impairment; and 5) define the progression of this disorder.